Low-resolution vehicle image recognition technology by frame composition of moving images
| Autor: | Toshio Ito, Takenao Ohkawa, Hiroki Kobayashi, Yusuke Kanzawa |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Signal processing
Engineering Computer Networks and Communications business.industry Applied Mathematics Low resolution Frame (networking) Automotive industry General Physics and Astronomy Advanced driver assistance systems Image processing Iterative reconstruction Image (mathematics) Signal Processing Computer vision Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | Electronics and Communications in Japan. 93:1-7 |
| ISSN: | 1942-9541 1942-9533 |
| DOI: | 10.1002/ecj.10246 |
| Popis: | Developing on-board automotive driver assistance systems intended to alert drivers about driving environments, and about possible collisions with other vehicles, has been attracting considerable attention. In particular, many researchers have suggested forward vehicle recognition technology using a camera installed in the vehicle. In forward vehicle recognition, however, it is difficult to detect the features of a vehicle from a distant vehicle image by conventional methods, because the image is too low-resolution (LR). This paper presents a vehicle image recognition technology for detecting the features of a distant vehicle by frame composition of moving images. To detect the vehicle features from a distant LR vehicle image, we use moving images obtained from a camera installed on the vehicle, and utilize super-resolution (SR) image reconstruction. SR image reconstruction consists of using signal processing techniques to obtain a high-resolution (or sequence) image from observed multiple LR images. The use of this technique on real road images shows the effectiveness of the proposed techniques. © 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(3): 1–7, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10246 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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